System and method for finding regions of interest for microscopic digital montage imaging

ABSTRACT

A system for determining tissue locations on a slide.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.11/221,331 filed Sep. 6, 2005, which is a continuation of U.S. patentapplication Ser. No. 09/758,037, filed Jan. 11, 2001, now U.S. Pat. No.6,993,169, both of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

Laboratories in many biomedical specialties, such as anatomic pathology,hematology, and microbiology, examine tissue under a microscope for thepresence and the nature of disease. In recent years, these laboratorieshave shown a growing interest in microscopic digital imaging as anadjunct to direct visual examination. Digital imaging has a number ofadvantages including the ability to document disease, share findings,collaborate (as in telemedicine), and analyze morphologic findings bycomputer. Though numerous studies have shown that digital image qualityis acceptable for most clinical and research use, some aspects ofmicroscopic digital imaging are limited in application.

Perhaps the most important limitation to microscopic digital imaging isa “subsampling” problem encountered in all single frame images. Thesub-sampling problem has two components: a field of view problem and aresolution-based problem. The field of view problem occurs when aninvestigator looking at a single frame cannot determine what liesoutside the view of an image on a slide. The resolution-based problemoccurs when the investigator looking at an image is limited to theresolution of the image. The investigator cannot “zoom in” for a closerexamination or “zoom out” for a bird's eye view. Significantly, thefield of view and resolution-based problems are inversely related. Thus,as one increases magnification to improve resolution, one decreases thefield of view. For example, as a general rule, increasing magnificationby a factor of two decreases the field of view by a factor of four.

To get around the limitations of single frame imaging, developers havelooked at two general options. The first option takes the general formof “dynamic-robotic” imaging, in which a video camera on the microscopetransmits close to real time images to the investigator looking at amonitor, while the investigator operates the microscope by remotecontrol. Though such systems have been used successfully fortelepathology, they do not lend themselves to documentation,collaboration, or computer based analysis.

The second option being investigated to overcome the limitations inheritin single frame imaging is a montage (or “virtual slide”) approach. Inthis method, a robotic microscope systematically scans the entire slide,taking an image at every field. The individual images are then “knitted”together in a software application to form a very large data set withvery appealing properties. The robotic microscope can span the entireslide area at a resolution limited only by the power of the opticalsystem and camera. Software exists to display this data set at anyresolution on a computer screen, allowing the user to zoom in, zoom out,and pan around the data set as if using a physical microscope. The dataset can be stored for documentation, shared over the Internet, oranalyzed by computer programs.

The “virtual slide” option has some limitations, however. One of thelimitations is file size. For an average tissue section, the datagenerated at 0.33 um/pixel can be between two and five gigabytesuncompressed. In an extreme case, the data generated from one slide canbe up to thirty-six gigabytes.

A much more difficult limitation with the prior systems is an imagecapture time problem. Given an optical primary magnification of twentyand a two-third inch CCD, the system field of view is approximately (8.8mm.times.6.6 mm)/20=0.44.times.0.33 mm. A standard microscope slidetypically has a specimen area of 25 mm.times.50 mm or 12.5 squarecentimeters. This requires over eighty-six hundred fields to image thisentire specimen region. However, the average tissue section for anatomicpathology is approximately 2.25 square centimeters. This only requiresapproximately fifteen hundred fields to cover the tissue alone,approximately 80 percent less fields.

Traditionally, field rate in montage systems is limited by threefactors—camera frame rate, image processing speed, and the rate of slidemotion between fields. Given today's technology, the limiting factor canbe reduced to only the camera frame rate. Using a 10 frame per secondcamera for the example above, imaging the entire slide would require 860seconds or 14.33 minutes. If only the region of interest was imaged,this average time could be reduced to 150 seconds or 2.5 minutes;substantially increasing the slide throughput of an imaging system.

Thus, a system is needed to automatically find the region of interest ona microscope slide and image only this region.

FIELD OF THE INVENTION

The present invention relates to microscopic digital imaging of tissuesections for medical and research use. In particular it describes amethod to find regions of interest for high throughput montage imagingof microscope slides using a standard microscope and camera.

SUMMARY OF THE INVENTION

An embodiment of a tissue finding method disclosed herein includesdifferentiating tissue containing regions of a microscope slide fromnon-tissue containing regions of the microscope slide. An embodiment ofa tissue finding apparatus disclosed herein includes a device todifferentiate tissue containing regions of a microscope slide fromnon-tissue containing regions of the microscope slide.

The present invention relates to a method and system for processing athumbnail image from a microscope slide to determine tissue locations onthe slide. An embodiment of the system comprises an image croppingcomponent, a tissue finding component, and a scan control component. Theimage cropping component crops the thumbnail image and removes portionsof the image that fall outside of determined slide boundaries. Thecropped image from the image cropping component is inputted into thetissue finding component. The tissue finding component identifies tissueregions by applying a sequence of filters that incorporate knowledge oftypical appearance and location of tissue and non-tissue slide regions.The tissue finding component outputs a tiling matrix whose valuesindicate which tiles should be imaged. The scan control componentinterprets the tiling matrix and transposes positions of the tilingmatrix into actual stage coordinate for a microscopic imaging.

Accordingly, it is an object of an embodiment of the invention toprovide a microscopic imaging system for whole slide montage in whichstandard microscope optics, off the shelf cameras and a simple motorizedstage can be used to select the region of interest, image only thissection and produce aligned image tiles.

An embodiment of the present invention uses a pre-scan process appliedto a macroscopic image of the slide, to guide a high-resolution slidescanning process and ensure high-quality images of the entire specimenare acquired. The pre-scan process includes an image cropping component,a tissue-finding component, and a scan control component. The imagecropping and tissue finding components identify interesting regions onthe slide to be scanned. The scan control component generates thecontrol parameters for a motorized microscopic imaging system.

It is another object of an embodiment of the invention to use ahigh-resolution slide scanning process to control the operation of themotorized stage and camera. This process utilizes information gatheredby the pre-scan process, namely the imaging regions, to control thepositioning of the stage to image only the regions of interest and toensure the individual images are well aligned.

Additional features and advantages of the invention will be set forth inthe description that follows, and in part will be apparent from thedescription, or may be learned by practice of the invention. Theobjectives and advantages of the invention to be realized and attainedby the microscopic image capture system will be pointed out in thewritten description and claims hereof as well as the appended drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a furtherunderstanding of the invention and are incorporated in and constitute apart of this specification, illustrate embodiments of the invention thattogether with the description serve to explain the principles of theinvention.

FIG. 1 illustrates an isometric view of the system in an embodiment;

FIG. 2 represents sample results of the macroscopic image after thecropping component has been applied to remove non-slide regions;

FIG. 3 represents sample results of the find tissue component; and

FIG. 4 is an overlay of FIGS. 2 and 3 representing the regions of theslide to be imaged.

DETAILED DESCRIPTION OF THE DRAWINGS

Reference will now be made in detail to the preferred embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings. The following paragraphs describe the functionality of theinventive system and method for high throughput montage imaging ofmicroscope slides using a standard microscope and cameras.

FIG. 1 illustrates an embodiment of the invention. In this embodiment, aslide 112 to be imaged is placed on a thumbnail imaging position in aslide holder on a motorized stage 102. A single frame image containingthe entire slide is taken with a macro camera 106. This low-resolutionimage is analyzed by software components to determine the locations oftissue on slide 112. This information can then be used to generatecontrol parameters for stage 102 and microscopic camera 104 to ensurethat the scanning process captures high quality images of only thetissue regions, substantially reducing the time to scan an averageslide.

As is obvious to one skilled in the art, although capturing the singlemacroscopic image saves time, it is not necessary for the operation ofthe invention. Multiple macroscopic images may be required to generatecontrol parameters to the accuracy required based on the ratio of themacroscopic to microscopic magnifications and the camera specificationsof each camera, if separate cameras are utilized.

Specifically in an embodiment, a pre-scan processing of thelow-resolution or thumbnail image includes an image cropping component,a tissue-finding component and a scan control component. The imagecropping component and tissue finding component identify tissue regionson the slide to be scanned. The scan control component generates thenecessary control parameters to scan only the regions of interest underthe microscopic optics.

The first step in processing the thumbnail image may consist offlat-field correcting the macroscopic thumbnail image using a similarimage obtained from the same camera and a blank slide. This removes anyspatial light anomalies from the thumbnail image, which may reduce theefficiency of the tissue-finding component. Given the format, or size,of the camera and the aspect ratio of the slide, a portion of the imagewill contain non-slide objects such as the slide carrier. To removethese features, the thumbnail image may be cropped to extract only theslide information.

The image cropping may be accomplished via a two-pass process. The firstpass determines an approximate location of the slide boundary, and thesecond pass fine-tunes this estimate. The search for the boundary may beconducted over upper and lower intervals corresponding to the regionsexpected to contain the upper and lower slide edges, respectively. Forthis discussion, the slide or region of interest is assumed to bepositioned near the center, vertically, in the thumbnail image. Tofacilitate this and subsequent processing steps, a copy of the thumbnailimage may be converted to grayscale. The portion of the image fallingoutside of the identified slide boundary may be removed. It should benoted that the original color image may also be cropped at the estimatededge locations, and then uniformly reduced in size to produce a smallthumbnail image of the slide for rapid, visual slide identification.

Since the slide may not be oriented perfectly horizontal in the originalthumbnail image, the identified slide edges are likely to lie at anangle. Thus, even after cropping, there may be remnants of the slideedges or cover slip in the cropped image. Therefore, the image-croppingcomponent attempts to identify pixel blocks that likely contain theseremaining edges and flags these blocks as edges that will not beconsidered for high resolution imaging by the tissue finding component.

The resulting cropped grayscale image generated by the image-croppingcomponent serves as input to the tissue finding component. Thiscomponent locates regions in the thumbnail image that contain tissue ofinterest to a specialist. In order to minimize the time and storagespace required to accomplish high-resolution slide imaging, theinventive system captures only those regions of the slide that containtissue. Embodiments of this approach may require that regions containingtissue be identified in the thumbnail image.

The tissue finding component identifies tissue regions via a sequence offilters that incorporate knowledge of the typical appearance andlocation of tissue and non-tissue slide regions. Initial filtering stepsmay analyze the mean and standard deviation of the local pixelintensities. Pixel mean intensities may be used to differentiatetissue-containing regions from blank and other non-tissue regions, suchas those containing the slide label or other markings. The standarddeviation data may represent the amount of variation in pixel values andthus is a good indicator of the border between tissue and the blankslide. The mean and standard deviation data may be combined to generatea threshold value that is used to make an initial classification oftissue versus non-tissue. Subsequently, morphological filters may beapplied to refine the classification based on the size and position ofneighboring groups of potential tissue pixels.

The filters which comprise the tissue finding component process thepixels of the cropped grayscale thumbnail image in groups thatcorrespond to slide regions, or tiles, that can be imaged individuallyduring the high-resolution scanning process. These filters ensure thattiles only partially filled with tissue are classified astissue-containing tiles. The final output of the filter sequence is atiling matrix whose values indicate which tiles should be imaged; thetiling matrix subsequently guides the high-resolution scanning process.

The above description was based on using the mean and standard deviationof the local pixels as the basis for detecting regions of interest. Itis obvious to one skilled in the art that other image characteristicscan be also used to identify the specimen from non-items of interestsuch as dust and scratches.

This description was also based on processing a gray scale macroscopicimage, the same processing tools can be applied to each of the colorcomponents (traditionally, red, green and blue) of a color image.Additional processing tools can also be applied between the colorcomponents to refine the tissue finding accuracy and to remove featuressuch as labels and writing that are not critical to the application.

An example of the image cropping and find tissue processing is shown inFIGS. 2, 3 and 4. FIG. 2 illustrates the macroscopic image afterflat-field correction and image cropping. FIG. 3 illustrates the resultsof the find tissue component. The resulting tile matrix shown in FIG. 3has a one-to-one correspondence to the field of view of the microscopiccamera. White pixels, which may be associated with a binary 1, maysignify fields to be capture and black pixels may represent regions notto image. FIG. 4 illustrates an overlay FIGS. 2 and 3 representing thesections of the slide to be imaged. For this application (anatomicalpathology), it may be imperative to image all suspect regions that maycontain tissue, so conservative criteria were used in the find tissuecomponent, resulting in cover slip edges and writing etched into theslide to be identified as to be imaged. The savings in the acquisitiontime is representative by the ratio of the white to black areas of FIG.3. For this image, only 53% of the slide region is to be imaged,including the label and cover slip edges, and etched writing on theslide.

At the completion of the find tissue component, in this example, thescan control component interprets the find tissue tile matrix (FIG. 3)and transposes the positions into actual stage coordinates for themicroscopic imaging. A program running on a host computer controls theoperation by communicating with a stage controller and microscopiccamera 104. Actual scanning can occur in any fashion such as by rows orcolumns, or in a step fashion to image neighboring areas.

The foregoing description has been directed to specific embodiments ofthis invention. It will be apparent, however, that other variations andmodifications may be made to the described embodiments, with theattainment of some or all of their advantages. Therefore, it is theobject of the appended claims to cover all such variations andmodifications as come within the true spirit and scope of the invention.

1. A device for processing a low resolution image from a slide todetermine a specimen location on the slide, comprising: means forcropping the low resolution image to remove portions of the lowresolution image that correspond to non-slide objects, the means forcropping including means for determining a location of at least oneboundary by searching at least one interval corresponding to at leastone boundary region; means for tissue finding, wherein the means fortissue finding identifies a region containing the specimen by applying afilter that incorporates knowledge of typical appearance and location ofspecimen and non-specimen slide regions and outputs a result thatindicates which regions of the slide should be imaged, the result notincluding portions of the image falling outside of the boundary; andtransposing positions of the result into actual stage coordinates; andmeans for capturing a microscopic image at the actual stage coordinates.2. The device as claimed in claim 1, wherein the means for croppingdetermines a location of a slide boundary by searching upper and lowerintervals corresponding to boundary regions expected to contain upperand lower edges of the slide; and not including in the result portionsof the image falling outside of the slide boundary as determined.
 3. Thedevice as claimed in claim 1, further comprising means for converting acopy of the low resolution image to a grayscale image.
 4. The device asclaimed in claim 2, wherein the low resolution image is a color image,and further comprising means for cropping the color low resolution imageat the slide boundary.
 5. The device as claimed in claim 4, furthercomprising means for reducing the color image size to produce a smallthumbnail image of the specimen for rapid visual identification.
 6. Thedevice as claimed in claim 1, further comprising means for identifyingpixel blocks in the cropped image that are likely to contain remainingslide edge features; and means for flagging the remaining slide edgefeatures as edges that should not be considered for high resolutionimaging.
 7. The device as claimed in claim 1, further comprising: meansfor converting a copy of the low resolution image to grayscale; andmeans for analyzing at least one of mean and standard deviation of localpixel intensities to generate a threshold value.
 8. The device asclaimed in claim 7, further comprising means for using the local pixelintensity to differentiate tissue-containing regions from non-tissuecontaining regions.
 9. The device as claimed in claim 1, furthercomprising means for applying a morphological filter to the result toidentify slide regions that can be imaged individually during ahigh-resolution imaging process.
 10. The device as claimed in claim 1,further comprising means for flat-field correcting the low resolutionimage using a blank slide image to remove anomalies from the lowresolution image.
 11. A device for processing a low resolution image ofa microscope slide to determine a specimen location, comprising: acomputer implemented cropping component to remove portions of the lowresolution image that correspond to non-slide objects, the croppingcomponent including a computer implemented boundary locater thatidentifies a location of at least one boundary by searching at least oneinterval corresponding to at least one boundary region; a computerimplemented tissue finder, that identifies a region containing thespecimen by applying a filter that incorporates knowledge of typicalappearance and location of specimen and non-specimen slide regions andthat outputs a result that indicates which regions of the slide shouldbe imaged, the result not including portions of the image fallingoutside of the boundary and that further transposes positions of theresult into actual stage coordinates; and an image capture device thatcaptures a microscopic image at the actual stage coordinates.
 12. Thedevice of claim 11, wherein the cropping component determines a locationof the at least one boundary by searching upper and lower intervalscorresponding to boundary regions expected to contain upper and loweredges of the slide; and not including in the result portions of theimage falling outside of the determined at least one boundary.
 13. Thedevice as claimed in claim 11, further comprising a converter thatconverts a copy of the low resolution image to a grayscale image. 14.The device as claimed in claim 12, wherein the low resolution image is acolor image, and wherein the computer implemented cropping componentcrops the color low resolution image at the slide boundary.
 15. Thedevice as claimed in claim 14, further comprising a thumbnail imagegenerator that reduces the color image size to produce a small thumbnailimage of the specimen for rapid visual identification.
 16. The device asclaimed in claim 11, wherein the computer implemented cropping componentidentifies pixel blocks in the cropped image that are likely to containremaining slide edge features; and flags the features as edges thatshould not be considered for high resolution imaging.
 17. The device asclaimed in claim 11, wherein the computer implemented tissue finderconverts a copy of the low resolution image to grayscale; and analyzesat least one of mean and standard deviation of local pixel intensitiesto generate a threshold value.
 18. The device as claimed in claim 17,wherein the computer implemented tissue finder uses the local pixelintensity to differentiate tissue-containing regions from blank regionsand other non-tissue containing regions.
 19. The device as claimed inclaim 11, wherein the computer implemented tissue finder applies amorphological filter to the result to identify slide regions that can beimaged individually during a high-resolution imaging process.
 20. Thedevice as claimed in claim 11, wherein the computer implemented tissuefinder applies flat-field correction the low resolution image using ablank slide image to remove anomalies from the low resolution image.